Scippy

SCIP

Solving Constraint Integer Programs

probdata_scflp.c
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1 /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
2 /* */
3 /* This file is part of the program and library */
4 /* SCIP --- Solving Constraint Integer Programs */
5 /* */
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24 
25 /**@file probdata_scflp.c
26  * @brief Problem data for Stochastic Capacitated Facility Location problem
27  * @author Stephen J. Maher
28  *
29  * This file handles the main problem data used in that project. For more details see \ref SCFLP_PROBLEMDATA page.
30  *
31  * @page SCFLP_SOLVEPROB Solving the deterministic equivalent
32  *
33  * The probdata_scflp.c is used to store the global problem data and build the monolithic MIP and decomposed problems.
34  * First, the structure of the problem data is describe. This is followed by a description of how to solve the problem
35  * directly using SCIP or using Benders' decomposition.
36  *
37  * @section SCFLP_PROBLEMDATA The global problem data
38  *
39  * The problem data is accessible in all plugins. The function SCIPgetProbData() returns the pointer to that structure.
40  * We use this data structure to store all the information of the SCFLP. Since this structure is not visible in the
41  * other plugins, we implemented setter and getter functions to access this data. The problem data structure
42  * SCIP_ProbData is shown below.
43  *
44  * \code
45  * ** @brief Problem data which is accessible in all places
46  * *
47  * * This problem data is used to store the input of the cap instance, all variables which are created, and all
48  * * constraints. In addition, the probdata stores the data structures for the decomposed problem. This permits the
49  * * use of Benders' decomposition to solve the stochastic program.
50  * *
51  * struct SCIP_ProbData
52  * {
53  * SCIP** subproblems; **< the Benders' decomposition subproblems * SCIP_VAR**
54  * SCIP_VAR** facilityvars; **< all variables representing facilities *
55  * SCIP_VAR*** subfacilityvars; **< duplicates of the facility variables in the subproblems *
56  * SCIP_VAR**** customervars; **< all variables representing the satisfaction of demand per scenario *
57  * SCIP_CONS*** capconss; **< capacity constraints per facility per scenario *
58  * SCIP_CONS*** demandconss; **< demand constraints per customer per scenario *
59  * SCIP_CONS* sufficientcap; **< ensuring sufficient capacity is provided to satisfy demand (relatively complete recourse) *
60  * SCIP_Real** costs; **< the transportation costs to a customer from a facility *
61  * SCIP_Real** demands; **< the customer demands per scenario *
62  * SCIP_Real* capacity; **< the capacity of each facility *
63  * SCIP_Real* fixedcost; **< the fixed cost of opening each facility *
64  * int ncustomers; **< the number of customers *
65  * int nfacilities; **< the number of facilities *
66  * int nscenarios; **< the number of scenarios *
67  * SCIP_Bool usebenders; **< whether Benders' decomposition is used *
68  * };
69  * \endcode
70  *
71  * The function SCIPprobdataCreate() manages the creation of the SCFLP instance in SCIP. There are two types of
72  * formulations that can be produced in this example. The first is the monolithic deterministic equivalent. The second
73  * is the reformulated problem that decomposes the stochastic problem by scenarios. This alternative formulations is
74  * solved using Benders' decomposition. Depending on the solution method, some members of SCIP_ProbData will be unused.
75  * For example, subproblems and subfacilityvars are only used when Benders' decomposition is applied to solve the SCFLP.
76  *
77  * The probdata_scflp.c also provide interface methods to the global problem data. A list of all interface methods can be
78  * found in probdata_scflp.h.
79  *
80  * @section SCFLP_DETEQUIV Directly solving the deterministic equivalent using SCIP
81  *
82  * Within probdata_scflp.c, both the monolithic determinstic equivalent or the decomposed problem can be built within
83  * SCIP. The monolithic deterministic equivalent involve a since SCIP instances that is solved directly as a MIP. The
84  * problem that is build in SCIP is given in \ref SCFLP_DETEQUIVMODEL.
85  *
86  * @section SCFLP_BENDERS Solving the SCFLP using Benders' decomposition
87  *
88  * The model that is used to build the decomposed problem is given in \ref SCFLP_BENDERSMODEL. In this example, the
89  * default Benders' decomposition plugin is used to employ the Benders' decomposition framework, see
90  * src/scip/benders_default.h. Before calling SCIPcreateBendersDefault() to invoke the Benders' decomposition framework,
91  * the SCIP instances for the master problem and the subproblems must be created.
92  *
93  * The SCIP instance for the master problem includes only the first stage variables (the facility variables \f$x_{i}\f$)
94  * and the first stage constraints. Note, the auxiliary variables are not added to the master problem by the user, nor
95  * are any Benders' decomposition cuts.
96  *
97  * For each subproblem \f$s\f$, the SCIP instance is formulated with the second stage variables (the customer variables
98  * \f$y^{s}_{ij}\f$) and the second stage constraints. Also, the first stage variables are created for each scenario.
99  * These variables are copies of the master variables from the master SCIP instances and must be created by calling
100  * SCIPcreateVarBasic() or SCIPcreateVar(). The master problem variable copies that are created in the subproblem SCIP
101  * instances must have an objective coefficient of 0.0. This is inline with the classical application of Benders'
102  * decomposition.
103  *
104  * IMPORTANT: the master variables that are created for the subproblem SCIP instances must have the same name as the
105  * corresponding master variables in the master problem SCIP instance. This is because the mapping between the master
106  * and subproblem variables relies on the variable names. This mapping is used for setting up the subproblems to
107  * evaluate solutions from the master problem and generating Benders' cuts.
108  *
109  * Once the master and subproblem SCIP instances are created, the Benders' decomposition is invoked by calling the
110  * interface function SCIPcreateBendersDefault(). The parameters for this function are a SCIP instance for the master
111  * problem, an array of SCIP instances for the subproblems and the number of subproblems.
112  *
113  * The Benders' decomposition framework involves the use of constraint handlers within SCIP, src/scip/cons_benders.h and
114  * src/scip/cons_benderslp.h. In order to solve the master problem by adding Benders' cuts, src/scip/cons_benders.h and
115  * src/scip/cons_benderslp.h must be activated. This is done by setting the parameter "constraints/benders/active" and
116  * "constraints/benderslp/active" to TRUE.
117  *
118  * NOTE: it is not necessary to activate src/scip/cons_benderslp.h. The purpose of this constraint handler is to
119  * generate Benders' decomposition cut from solutions to the LP relaxation in the root node. These solutions are
120  * fractional, since the enforcement priority of benderslp is higher than the integer constraint handler. The benderslp
121  * constraint handler allows the user to employ the multi-phase algorithm of McDaniel and Devine (1977).
122  *
123  * McDaniel D, Devine M. A modified Benders’ partitioning algorithm for mixed integer programming. Management Science
124  * 1977;24(2):312–9
125  */
126 
127 /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
128 
129 #include <string.h>
130 
131 #include "probdata_scflp.h"
132 
133 #include "scip/scip.h"
134 #include "scip/scipdefplugins.h"
135 
136 #define DEFAULT_SCALINGFACTOR 5000.0
137 
138 /** @brief Problem data which is accessible in all places
139  *
140  * This problem data is used to store the input of the SCFLP, all variables which are created, and all constraints.
141  */
142 struct SCIP_ProbData
143 {
144  SCIP** subproblems; /**< the Benders' decomposition subproblems */
145  SCIP_VAR** facilityvars; /**< all variables representing facilities */
146  SCIP_VAR*** subfacilityvars; /**< duplicates of the facility variables in the subproblems */
147  SCIP_VAR**** customervars; /**< all variables representing the satisfaction of demand per scenario */
148  SCIP_CONS*** capconss; /**< capacity constraints per facility per scenario */
149  SCIP_CONS*** demandconss; /**< demand constraints per customer per scenario */
150  SCIP_CONS* sufficientcap; /**< ensuring sufficient capacity is provided to satisfy demand (relatively complete recourse) */
151  SCIP_Real** costs; /**< the transportation costs to a customer from a facility */
152  SCIP_Real** demands; /**< the customer demands per scenario */
153  SCIP_Real* capacity; /**< the capacity of each facility */
154  SCIP_Real* fixedcost; /**< the fixed cost of opening each facility */
155  int ncustomers; /**< the number of customers */
156  int nfacilities; /**< the number of facilities */
157 
158  /* probdata parameters */
159  int nscenarios; /**< the number of scenarios */
160  SCIP_Bool usebenders; /**< whether Benders' decomposition is used */
161  SCIP_Bool quadcosts; /**< should the problem be formulated with quadratic costs */
162 };
163 
164 
165 
166 /**@name Local methods
167  *
168  * @{
169  */
170 
171 /** creates the original problem */
172 static
174  SCIP* scip, /**< SCIP data structure */
175  SCIP_VAR** facilityvars, /**< all variables representing facilities */
176  SCIP_VAR**** customervars, /**< all variables representing the satisfaction of demand */
177  SCIP_CONS*** capconss, /**< capacity constraints per facility */
178  SCIP_CONS*** demandconss, /**< demand constraints per customer */
179  SCIP_CONS** sufficientcap, /**< ensuring sufficient capacity is provided to satisfy demand */
180  SCIP_Real** costs, /**< the transportation costs from a facility to a customer */
181  SCIP_Real** demands, /**< the customer demands */
182  SCIP_Real* capacity, /**< the capacity of each facility */
183  SCIP_Real* fixedcost, /**< the fixed cost of opening a facility */
184  int ncustomers, /**< the number of customers */
185  int nfacilities, /**< the number of facilities */
186  int nscenarios, /**< the number of scenarios */
187  SCIP_Bool quadcosts /**< should the problem be formulated with quadratic costs */
188  )
189 {
190  SCIP_CONS* cons;
191  SCIP_VAR* var;
192  SCIP_VAR* sqrvar;
193  SCIP_Real maxdemand;
194  SCIP_Real coeff;
195  SCIP_Real custcoeff;
196  SCIP_Real one = 1.0;
197  SCIP_Real minusone = -1.0;
198  int i;
199  int j;
200  int k;
201  char name[SCIP_MAXSTRLEN];
202 
203 
204  assert(scip != NULL);
205 
206  /* adding the sufficient capacity constraints */
207  maxdemand = 0;
208  for( i = 0; i < nscenarios; i++)
209  {
210  SCIP_Real sumdemand = 0;
211  for( j = 0; j < ncustomers; j++ )
212  sumdemand += demands[j][i];
213 
214  if( sumdemand > maxdemand )
215  maxdemand = sumdemand;
216  }
217 
218  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "sufficientcapacity");
219  SCIP_CALL( SCIPcreateConsBasicLinear(scip, sufficientcap, name, 0, NULL, NULL, maxdemand, SCIPinfinity(scip)) );
220 
221  SCIP_CALL( SCIPaddCons(scip, (*sufficientcap)) );
222 
223  /* adds the capacity constraints to the scenario */
224  for( i = 0; i < nfacilities; i++ )
225  {
226  for( j = 0; j < nscenarios; j++ )
227  {
228  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "capacity_%d_%d", i, j);
229  SCIP_CALL( SCIPcreateConsBasicLinear(scip, &cons, name, 0, NULL, NULL, -SCIPinfinity(scip), 0.0) );
230 
231  SCIP_CALL( SCIPaddCons(scip, cons) );
232 
233  capconss[i][j] = cons;
234  }
235  }
236 
237  /* adds the demand constraints to the scenario */
238  for( i = 0; i < ncustomers; i++ )
239  {
240  for( j = 0; j < nscenarios; j++ )
241  {
242  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "demand_%d_%d", i, j);
243  SCIP_CALL( SCIPcreateConsBasicLinear(scip, &cons, name, 0, NULL, NULL, demands[i][j], SCIPinfinity(scip)) );
244 
245  SCIP_CALL( SCIPaddCons(scip, cons) );
246 
247  demandconss[i][j] = cons;
248  }
249  }
250 
251  for( i = 0; i < nfacilities; i++ )
252  {
253  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "facility_%d", i);
254  SCIP_CALL( SCIPcreateVarBasic(scip, &var, name, 0.0, 1.0, fixedcost[i], SCIP_VARTYPE_BINARY) );
255 
256  SCIP_CALL( SCIPaddVar(scip, var) );
257 
258  /* storing the variable in the facility variable list */
259  facilityvars[i] = var;
260 
261  /* adding the variable to the capacity constraints */
262  for( j = 0; j < nscenarios; j++ )
263  SCIP_CALL( SCIPaddCoefLinear(scip, capconss[i][j], var, -capacity[i]) );
264 
265  /* adding the variable to the sufficient capacity constraints */
266  SCIP_CALL( SCIPaddCoefLinear(scip, (*sufficientcap), var, capacity[i]) );
267  }
268 
269  /* adding the customer variables to the scenario */
270  for( i = 0; i < ncustomers; i++ )
271  {
272  for( j = 0; j < nfacilities; j++ )
273  {
274  for( k = 0; k < nscenarios; k++ )
275  {
276  custcoeff = costs[i][j]/(SCIP_Real)nscenarios;
277 
278  /* if the quadratic costs are used, then the customer coefficient is zero and the quadratic costs are scaled
279  * by 10,000. */
280  if( quadcosts )
281  {
282  coeff = custcoeff / DEFAULT_SCALINGFACTOR;
283  custcoeff = 0.0;
284  }
285 
286  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customer(%d,%d,%d)", i, j, k);
287  SCIP_CALL( SCIPcreateVarBasic(scip, &var, name, 0.0, SCIPinfinity(scip), custcoeff,
289 
290  SCIP_CALL( SCIPaddVar(scip, var) );
291 
292  /* storing the customer variable in the list */
293  customervars[i][j][k] = var;
294 
295  if( costs[i][j] > 0 )
296  {
297  /* adding the variable to the capacity constraints */
298  SCIP_CALL( SCIPaddCoefLinear(scip, capconss[j][k], customervars[i][j][k], 1.0) );
299 
300  /* adding the variable to the demand constraints */
301  SCIP_CALL( SCIPaddCoefLinear(scip, demandconss[i][k], customervars[i][j][k], 1.0) );
302 
303  /* if the quadratic costs are used, then variables representing the square of the customer supply
304  * must be added
305  */
306  if( quadcosts )
307  {
308  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customersqr(%d,%d,%d)", i, j, k);
309  SCIP_CALL( SCIPcreateVarBasic(scip, &sqrvar, name, 0.0, SCIPinfinity(scip), coeff, SCIP_VARTYPE_CONTINUOUS) );
310 
311  SCIP_CALL( SCIPaddVar(scip, sqrvar) );
312 
313  /* add constraint var^2 <= sqrvar */
314  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customersqrcons(%d,%d,%d)", i, j, k);
315  SCIP_CALL( SCIPcreateConsQuadraticNonlinear(scip, &cons, name, 1, &sqrvar, &minusone, 1, &var, &var,
316  &one, -SCIPinfinity(scip), 0.0, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
317 
318  SCIP_CALL( SCIPaddCons(scip, cons) );
319 
320  SCIP_CALL( SCIPreleaseCons(scip, &cons) );
321  SCIP_CALL( SCIPreleaseVar(scip, &sqrvar) );
322  }
323  }
324  }
325  }
326  }
327 
328  return SCIP_OKAY;
329 }
330 
331 /** creates the Benders' decomposition master problem */
332 static
334  SCIP* scip, /**< SCIP data structure */
335  SCIP_VAR** facilityvars, /**< all variables representing facilities */
336  SCIP_CONS** sufficientcap, /**< ensuring sufficient capacity is provided to satisfy demand */
337  SCIP_Real* capacity, /**< the capacity of each facility */
338  SCIP_Real* fixedcost, /**< the fixed cost of opening a facility */
339  SCIP_Real** demands, /**< the customer demands */
340  int ncustomers, /**< the number of customers */
341  int nfacilities, /**< the number of facilities */
342  int nscenarios /**< the number of scenarios */
343  )
344 {
345  SCIP_VAR* var;
346  SCIP_Real maxdemand;
347  int i;
348  int j;
349  char name[SCIP_MAXSTRLEN];
350  assert(scip != NULL);
351 
353  "Creating the master problem\n============\n");
354 
355  /* adding the sufficient capacity constraints */
356  maxdemand = 0;
357  for( i = 0; i < nscenarios; i++)
358  {
359  SCIP_Real sumdemand = 0;
360  for( j = 0; j < ncustomers; j++ )
361  sumdemand += demands[j][i];
362 
363  if( sumdemand > maxdemand )
364  maxdemand = sumdemand;
365  }
366 
367  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "sufficientcapacity");
368  SCIP_CALL( SCIPcreateConsBasicLinear(scip, sufficientcap, name, 0, NULL, NULL, maxdemand, SCIPinfinity(scip)) );
369 
370  SCIP_CALL( SCIPaddCons(scip, (*sufficientcap)) );
371 
372  /* adding the facility variables */
373  for( i = 0; i < nfacilities; i++ )
374  {
375  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "facility_%d", i);
376  SCIP_CALL( SCIPcreateVarBasic(scip, &var, name, 0.0, 1.0, fixedcost[i], SCIP_VARTYPE_BINARY) );
377 
378  SCIP_CALL( SCIPaddVar(scip, var) );
379 
380  /* storing the variable in the facility variable list */
381  facilityvars[i] = var;
382 
383  /* adding the variable to the sufficient capacity constraints */
384  SCIP_CALL( SCIPaddCoefLinear(scip, (*sufficientcap), var, capacity[i]) );
385  }
386 
388  "master problem has %d binary variables and 1 constraint\n\n", nfacilities);
389 
390  return SCIP_OKAY;
391 }
392 
393 /** creates the scenario subproblems */
394 static
396  SCIP* scip, /**< SCIP data structure */
397  SCIP** subproblems, /**< the Benders' decomposition subproblems */
398  SCIP_VAR** facilityvars, /**< all variables representing facilities */
399  SCIP_VAR*** subfacilityvars, /**< the copies of the facility variables in the subproblems */
400  SCIP_VAR**** customervars, /**< all variables representing the satisfaction of demand */
401  SCIP_CONS*** capconss, /**< capacity constraints per facility */
402  SCIP_CONS*** demandconss, /**< demand constraints per customer */
403  SCIP_Real** costs, /**< the transportation costs from a facility to a customer */
404  SCIP_Real** demands, /**< the customer demands */
405  SCIP_Real* capacity, /**< the capacity of each facility */
406  SCIP_Real* fixedcost, /**< the fixed cost of opening a facility */
407  int ncustomers, /**< the number of customers */
408  int nfacilities, /**< the number of facilities */
409  int nscenarios, /**< the number of scenarios */
410  SCIP_Bool quadcosts /**< should the problem be formulated with quadratic costs */
411  )
412 {
413  SCIP_CONS* cons;
414  SCIP_VAR* var;
415  SCIP_VAR* sqrvar;
416  SCIP_Real coeff;
417  SCIP_Real custcoeff;
418  SCIP_Real one = 1.0;
419  SCIP_Real minusone = -1.0;
420  int i;
421  int j;
422  int k;
423  char name[SCIP_MAXSTRLEN];
424 
425 
426  assert(scip != NULL);
427 
429  "Creating the subproblems\n============\n");
430 
431  /* adds the capacity constraints to the scenario */
432  for( i = 0; i < nfacilities; i++ )
433  {
434  for( j = 0; j < nscenarios; j++ )
435  {
436  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "capacity_%d_%d", i, j);
437  SCIP_CALL( SCIPcreateConsBasicLinear(subproblems[j], &cons, name, 0, NULL, NULL, -SCIPinfinity(subproblems[j]), 0.0) );
438 
439  SCIP_CALL( SCIPaddCons(subproblems[j], cons) );
440 
441  capconss[i][j] = cons;
442  }
443  }
444 
445  /* adds the demand constraints to the scenario */
446  for( i = 0; i < ncustomers; i++ )
447  {
448  for( j = 0; j < nscenarios; j++ )
449  {
450  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "demand_%d_%d", i, j);
451  SCIP_CALL( SCIPcreateConsBasicLinear(subproblems[j], &cons, name, 0, NULL, NULL, demands[i][j], SCIPinfinity(subproblems[j])) );
452 
453  SCIP_CALL( SCIPaddCons(subproblems[j], cons) );
454 
455  demandconss[i][j] = cons;
456  }
457  }
458 
459  for( i = 0; i < nfacilities; i++ )
460  {
461  for( j = 0; j < nscenarios; j++ )
462  {
463  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "facility_%d", i);
464  SCIP_CALL( SCIPcreateVarBasic(subproblems[j], &var, name, 0.0, 1.0, 0.0, SCIP_VARTYPE_CONTINUOUS) );
465 
466  SCIP_CALL( SCIPaddVar(subproblems[j], var) );
467 
468  /* storing the variable in the facility variable list */
469  subfacilityvars[i][j] = var;
470 
471  /* adding the variable to the capacity constraints */
472  SCIP_CALL( SCIPaddCoefLinear(subproblems[j], capconss[i][j], subfacilityvars[i][j], -capacity[i]) );
473  }
474  }
475 
476  /* adding the customer variables to the scenario */
477  for( i = 0; i < ncustomers; i++ )
478  {
479  for( j = 0; j < nfacilities; j++ )
480  {
481  for( k = 0; k < nscenarios; k++ )
482  {
483  custcoeff = costs[i][j]/(SCIP_Real)nscenarios;
484 
485  /* if the quadratic costs are used, then the customer coefficient is zero and the quadratic costs are scaled
486  * by 10,000. */
487  if( quadcosts )
488  {
489  coeff = custcoeff / 10000.0;
490  custcoeff = 0.0;
491  }
492 
493  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customer(%d,%d,%d)", i, j, k);
494  SCIP_CALL( SCIPcreateVarBasic(subproblems[k], &var, name, 0.0, SCIPinfinity(subproblems[k]), custcoeff,
496 
497  SCIP_CALL( SCIPaddVar(subproblems[k], var) );
498 
499  /* storing the customer variable in the list */
500  customervars[i][j][k] = var;
501 
502  if( costs[i][j] > 0 )
503  {
504  /* adding the variable to the capacity constraints */
505  SCIP_CALL( SCIPaddCoefLinear(subproblems[k], capconss[j][k], customervars[i][j][k], 1.0) );
506 
507  /* adding the variable to the demand constraints */
508  SCIP_CALL( SCIPaddCoefLinear(subproblems[k], demandconss[i][k], customervars[i][j][k], 1.0) );
509 
510 
511  /* if the quadratic costs are used, then variables representing the square of the customer supply
512  * must be added
513  */
514  if( quadcosts )
515  {
516  coeff = costs[i][j]/(SCIP_Real)nscenarios / DEFAULT_SCALINGFACTOR;
517  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customersqr(%d,%d,%d)", i, j, k);
518  SCIP_CALL( SCIPcreateVarBasic(subproblems[k], &sqrvar, name, 0.0, SCIPinfinity(subproblems[k]), coeff, SCIP_VARTYPE_CONTINUOUS) );
519 
520  SCIP_CALL( SCIPaddVar(subproblems[k], sqrvar) );
521 
522  /* add constraint var^2 <= sqrvar */
523  (void) SCIPsnprintf(name, SCIP_MAXSTRLEN, "customersqrcons(%d,%d,%d)", i, j, k);
524  SCIP_CALL( SCIPcreateConsQuadraticNonlinear(subproblems[k], &cons, name, 1, &sqrvar, &minusone, 1, &var, &var, &one, -SCIPinfinity(subproblems[k]), 0.0, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
525 
526  SCIP_CALL( SCIPaddCons(subproblems[k], cons) );
527 
528  SCIP_CALL( SCIPreleaseCons(subproblems[k], &cons) );
529  SCIP_CALL( SCIPreleaseVar(subproblems[k], &sqrvar) );
530  }
531  }
532  }
533  }
534  }
535 
537  "%d subproblems have been created.\neach subproblem has %d continuous variables and %d constraint\n\n",
538  nscenarios, ncustomers*nfacilities + nfacilities, nfacilities + ncustomers);
539 
540  return SCIP_OKAY;
541 }
542 
543 
544 /** creates problem data */
545 static
547  SCIP* scip, /**< SCIP data structure */
548  SCIP_PROBDATA** probdata, /**< pointer to problem data */
549  SCIP** subproblems, /**< the Benders' decomposition subproblems */
550  SCIP_VAR** facilityvars, /**< all variables representing facilities */
551  SCIP_VAR*** subfacilityvars, /**< the copies of the facility variables in the subproblems */
552  SCIP_VAR**** customervars, /**< all variables representing the satisfaction of demand */
553  SCIP_CONS*** capconss, /**< capacity constraints per facility per scenario */
554  SCIP_CONS*** demandconss, /**< demand constraints per customer per scenario */
555  SCIP_CONS* sufficientcap, /**< ensuring sufficient capacity is provided to satisfy demand */
556  SCIP_Real** costs, /**< the transportation costs to a customer from a facility */
557  SCIP_Real** demands, /**< the customer demands per scenario */
558  SCIP_Real* capacity, /**< the capacity of each facility */
559  SCIP_Real* fixedcost, /**< the fixed cost of opening a facility */
560  int ncustomers, /**< the number of customers */
561  int nfacilities, /**< the number of facilities */
562  int nscenarios, /**< the number of scenarios */
563  SCIP_Bool usebenders, /**< whether Benders' decomposition is used */
564  SCIP_Bool quadcosts /**< should the problem be formulated with quadratic costs */
565  )
566 {
567  int i;
568  int j;
569 
570  assert(scip != NULL);
571  assert(probdata != NULL);
572 
573  /* allocate memory */
574  SCIP_CALL( SCIPallocBlockMemory(scip, probdata) );
575 
576  /* copying the subproblem information */
577  if( usebenders )
578  {
579  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->subproblems, subproblems, nscenarios) );
580 
581  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->subfacilityvars, nfacilities) );
582  for( i = 0; i < nfacilities; i++ )
583  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->subfacilityvars[i], subfacilityvars[i], nscenarios) );
584  }
585 
586  /* copy variable arrays */
587  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->facilityvars, facilityvars, nfacilities) );
588  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->customervars, ncustomers) );
589  for( i = 0; i < ncustomers; i++ )
590  {
591  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->customervars[i], nfacilities) );
592  for( j = 0; j < nfacilities; j++ )
593  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->customervars[i][j], customervars[i][j],
594  nscenarios) );
595  }
596 
597  /* duplicate the constraint arrays */
598  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->capconss, nfacilities) );
599  for( i = 0; i < nfacilities; i++ )
600  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->capconss[i], capconss[i], nscenarios) );
601 
602  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->demandconss, ncustomers) );
603  for( i = 0; i < ncustomers; i++ )
604  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->demandconss[i], demandconss[i], nscenarios) );
605 
606  /* duplicate the data arrays */
607  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->demands, ncustomers) );
608  for( i = 0; i < ncustomers; i++ )
609  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->demands[i], demands[i], nscenarios) );
610 
611  SCIP_CALL( SCIPallocBlockMemoryArray(scip, &(*probdata)->costs, ncustomers) );
612  for( i = 0; i < ncustomers; i++ )
613  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->costs[i], costs[i], nfacilities) );
614 
615  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->capacity, capacity, nfacilities) );
616  SCIP_CALL( SCIPduplicateBlockMemoryArray(scip, &(*probdata)->fixedcost, fixedcost, nfacilities) );
617 
618  (*probdata)->sufficientcap = sufficientcap;
619  (*probdata)->ncustomers = ncustomers;
620  (*probdata)->nfacilities = nfacilities;
621  (*probdata)->nscenarios = nscenarios;
622  (*probdata)->usebenders = usebenders;
623  (*probdata)->quadcosts = quadcosts;
624 
625  return SCIP_OKAY;
626 }
627 
628 /** frees the memory of the given problem data */
629 static
631  SCIP* scip, /**< SCIP data structure */
632  SCIP_PROBDATA** probdata /**< pointer to problem data */
633  )
634 {
635  int i;
636  int j;
637  int k;
638 
639  assert(scip != NULL);
640  assert(probdata != NULL);
641 
642 #if 1
643  /* release all variables */
644  for( i = 0; i < (*probdata)->nfacilities; i++ )
645  SCIP_CALL( SCIPreleaseVar(scip, &(*probdata)->facilityvars[i]) );
646 
647  for( i = 0; i < (*probdata)->nscenarios; i++ )
648  {
649  SCIP* varscip;
650  if( (*probdata)->usebenders )
651  varscip = (*probdata)->subproblems[i];
652  else
653  varscip = scip;
654 
655  for( j = 0; j < (*probdata)->nfacilities; j++ )
656  {
657  for( k = 0; k < (*probdata)->ncustomers; k++ )
658  SCIP_CALL( SCIPreleaseVar(varscip, &(*probdata)->customervars[k][j][i]) );
659  }
660  }
661 
662  /* release all constraints */
663  for( i = 0; i < (*probdata)->nscenarios; ++i )
664  {
665  SCIP* consscip;
666  if( (*probdata)->usebenders )
667  consscip = (*probdata)->subproblems[i];
668  else
669  consscip = scip;
670 
671  for( j = 0; j < (*probdata)->ncustomers; j++ )
672  SCIP_CALL( SCIPreleaseCons(consscip, &(*probdata)->demandconss[j][i]) );
673  }
674 
675  for( i = 0; i < (*probdata)->nscenarios; ++i )
676  {
677  SCIP* consscip;
678  if( (*probdata)->usebenders )
679  consscip = (*probdata)->subproblems[i];
680  else
681  consscip = scip;
682 
683  for( j = 0; j < (*probdata)->nfacilities; ++j )
684  SCIP_CALL( SCIPreleaseCons(consscip, &(*probdata)->capconss[j][i]) );
685  }
686 
687  SCIP_CALL( SCIPreleaseCons(scip, &(*probdata)->sufficientcap) );
688 #endif
689 
690  /* free memory of arrays */
691  SCIPfreeBlockMemoryArray(scip, &(*probdata)->fixedcost, (*probdata)->nfacilities);
692  SCIPfreeBlockMemoryArray(scip, &(*probdata)->capacity, (*probdata)->nfacilities);
693 
694  for( i = (*probdata)->ncustomers - 1; i >= 0; i-- )
695  SCIPfreeBlockMemoryArray(scip, &(*probdata)->costs[i], (*probdata)->nfacilities);
696  SCIPfreeBlockMemoryArray(scip, &(*probdata)->costs, (*probdata)->ncustomers);
697 
698  for( i = (*probdata)->ncustomers - 1; i >= 0; i-- )
699  SCIPfreeBlockMemoryArray(scip, &(*probdata)->demands[i], (*probdata)->nscenarios);
700  SCIPfreeBlockMemoryArray(scip, &(*probdata)->demands, (*probdata)->ncustomers);
701 
702  /* freeing the constraint memory arrays */
703  for( i = (*probdata)->ncustomers - 1; i >= 0; i-- )
704  SCIPfreeBlockMemoryArray(scip, &(*probdata)->demandconss[i], (*probdata)->nscenarios);
705  SCIPfreeBlockMemoryArray(scip, &(*probdata)->demandconss, (*probdata)->ncustomers);
706 
707  for( i = (*probdata)->nfacilities - 1; i >= 0; i-- )
708  SCIPfreeBlockMemoryArray(scip, &(*probdata)->capconss[i], (*probdata)->nscenarios);
709  SCIPfreeBlockMemoryArray(scip, &(*probdata)->capconss, (*probdata)->nfacilities);
710 
711  /* freeing the variable memory arrays */
712  for( i = (*probdata)->ncustomers - 1; i >= 0; i-- )
713  {
714  for( j = (*probdata)->nfacilities - 1; j >= 0; j-- )
715  SCIPfreeBlockMemoryArray(scip, &(*probdata)->customervars[i][j], (*probdata)->nscenarios);
716 
717  SCIPfreeBlockMemoryArray(scip, &(*probdata)->customervars[i], (*probdata)->nfacilities);
718  }
719  SCIPfreeBlockMemoryArray(scip, &(*probdata)->customervars, (*probdata)->ncustomers);
720 
721  SCIPfreeBlockMemoryArray(scip, &(*probdata)->facilityvars, (*probdata)->nfacilities);
722 
723  /* freeing the subproblem information */
724  if( (*probdata)->usebenders )
725  {
726  /* freeing the sub facility variables */
727  for( i = 0; i < (*probdata)->nscenarios; i++ )
728  {
729  for( j = 0; j < (*probdata)->nfacilities; j++ )
730  SCIP_CALL( SCIPreleaseVar((*probdata)->subproblems[i], &(*probdata)->subfacilityvars[j][i]) );
731  }
732 
733  for( i = (*probdata)->nfacilities - 1; i >= 0; i-- )
734  SCIPfreeBlockMemoryArray(scip, &(*probdata)->subfacilityvars[i], (*probdata)->nscenarios);
735 
736  SCIPfreeBlockMemoryArray(scip, &(*probdata)->subfacilityvars, (*probdata)->nfacilities);
737 
738  for( i = (*probdata)->nscenarios - 1; i >= 0 ; i-- )
739  SCIP_CALL( SCIPfree(&(*probdata)->subproblems[i]) );
740  SCIPfreeBlockMemoryArray(scip, &(*probdata)->subproblems, (*probdata)->nscenarios);
741  }
742 
743  /* free probdata */
744  SCIPfreeBlockMemory(scip, probdata);
745 
746  return SCIP_OKAY;
747 }
748 
749 /**@} */
750 
751 /**@name Callback methods of problem data
752  *
753  * @{
754  */
755 
756 /** frees user data of original problem (called when the original problem is freed) */
757 static
758 SCIP_DECL_PROBDELORIG(probdelorigScflp)
759 {
760  assert(scip != NULL);
761  assert(probdata != NULL);
762 
763  SCIPdebugMsg(scip, "free original problem data\n");
764 
765  SCIP_CALL( probdataFree(scip, probdata) );
766 
767  return SCIP_OKAY;
768 }
769 
770 /** creates user data of transformed problem by transforming the original user problem data
771  * (called after problem was transformed) */
772 static
773 SCIP_DECL_PROBTRANS(probtransScflp)
774 {
775  SCIPdebugMsg(scip, "transforming problem data\n");
776 
777  return SCIP_OKAY;
778 }
779 
780 /** frees user data of transformed problem (called when the transformed problem is freed) */
781 static
782 SCIP_DECL_PROBDELTRANS(probdeltransScflp)
783 {
784  SCIPdebugMsg(scip, "free transformed problem data\n");
785 
786  return SCIP_OKAY;
787 }
788 
789 /**@} */
790 
791 
792 /**@name Interface methods
793  *
794  * @{
795  */
796 
797 /** sets up the problem data */
799  SCIP* scip, /**< SCIP data structure */
800  const char* probname, /**< problem name */
801  SCIP_Real** costs, /**< the transportation costs from a facility to a customer */
802  SCIP_Real** demands, /**< the customer demands */
803  SCIP_Real* capacity, /**< the capacity of each facility */
804  SCIP_Real* fixedcost, /**< the fixed cost of opening a facility */
805  int ncustomers, /**< the number of customers */
806  int nfacilities, /**< the number of facilities */
807  int nscenarios, /**< the number of Benders' decomposition scenarios */
808  SCIP_Bool usebenders, /**< whether Benders' decomposition is used */
809  SCIP_Bool quadcosts /**< should the problem be formulated with quadratic costs */
810  )
811 {
812  SCIP** subproblems;
813  SCIP_PROBDATA* probdata;
814  SCIP_CONS*** demandconss;
815  SCIP_CONS*** capconss;
816  SCIP_CONS* sufficientcap;
817  SCIP_VAR** facilityvars;
818  SCIP_VAR*** subfacilityvars;
819  SCIP_VAR**** customervars;
820  int i;
821  int j;
822 
823  assert(scip != NULL);
824 
825  /* create problem in SCIP and add non-NULL callbacks via setter functions */
826  SCIP_CALL( SCIPcreateProbBasic(scip, probname) );
827 
828  SCIP_CALL( SCIPsetProbDelorig(scip, probdelorigScflp) );
829  SCIP_CALL( SCIPsetProbTrans(scip, probtransScflp) );
830  SCIP_CALL( SCIPsetProbDeltrans(scip, probdeltransScflp) );
831 
832  /* set objective sense */
834 
835  SCIP_CALL( SCIPallocBufferArray(scip, &demandconss, ncustomers) );
836  for( i = 0; i < ncustomers; i++ )
837  SCIP_CALL( SCIPallocBufferArray(scip, &demandconss[i], nscenarios) );
838  SCIP_CALL( SCIPallocBufferArray(scip, &capconss, nfacilities) );
839  for( i = 0; i < nfacilities; i++ )
840  SCIP_CALL( SCIPallocBufferArray(scip, &capconss[i], nscenarios) );
841 
842  SCIP_CALL( SCIPallocBufferArray(scip, &facilityvars, nfacilities) );
843  SCIP_CALL( SCIPallocBufferArray(scip, &customervars, ncustomers) );
844  for( i = 0; i < ncustomers; i++ )
845  {
846  SCIP_CALL( SCIPallocBufferArray(scip, &customervars[i], nfacilities) );
847  for( j = 0; j < nfacilities; j++ )
848  SCIP_CALL( SCIPallocBufferArray(scip, &customervars[i][j], nscenarios) );
849  }
850 
851  sufficientcap = NULL;
852 
853  subproblems = NULL;
854  subfacilityvars = NULL;
855 
856  /* if quadratic costs are used, then the costs are scaled by 10,000. The user must be informed about this scaling */
857  if( quadcosts )
858  {
859  SCIPinfoMessage(scip, NULL, "The problem will be formulated with quadratic costs. "
860  "The input costs will be scaled by %g\n\n", DEFAULT_SCALINGFACTOR);
861  }
862 
863  if( usebenders )
864  {
865  char subprobname[SCIP_MAXSTRLEN];
866 
867  /* allocting the memory for the subproblem specific information */
868  SCIP_CALL( SCIPallocBufferArray(scip, &subproblems, nscenarios) );
869  SCIP_CALL( SCIPallocBufferArray(scip, &subfacilityvars, nfacilities) );
870  for( i = 0; i < nfacilities; i++ )
871  SCIP_CALL( SCIPallocBufferArray(scip, &subfacilityvars[i], nscenarios) );
872 
873  /* creating the subproblems */
874  for( i = 0; i < nscenarios; i++ )
875  {
876  SCIP_CALL( SCIPcreate(&subproblems[i]) );
877 
878  /* include default SCIP plugins */
879  SCIP_CALL( SCIPincludeDefaultPlugins(subproblems[i]) );
880 
881  (void) SCIPsnprintf(subprobname, SCIP_MAXSTRLEN, "sub_%s_%d", probname, i);
882  SCIP_CALL( SCIPcreateProbBasic(subproblems[i], subprobname) );
883  }
884 
885  /* creating the master problem */
886  SCIP_CALL( createMasterproblem(scip, facilityvars, &sufficientcap, capacity, fixedcost, demands, ncustomers,
887  nfacilities, nscenarios) );
888  SCIP_CALL( createSubproblems(scip, subproblems, facilityvars, subfacilityvars, customervars, capconss,
889  demandconss, costs, demands, capacity, fixedcost, ncustomers, nfacilities, nscenarios, quadcosts) );
890 
891  /* including the Benders' decomposition plugin */
892  SCIP_CALL( SCIPcreateBendersDefault(scip, subproblems, nscenarios) );
893 
894  /* activating the Benders' decomposition constraint handlers */
895  SCIP_CALL( SCIPsetBoolParam(scip, "constraints/benders/active", TRUE) );
896  SCIP_CALL( SCIPsetBoolParam(scip, "constraints/benderslp/active", TRUE) );
897 
898  SCIP_CALL( SCIPsetIntParam(scip, "constraints/benders/maxprerounds", 1) );
899  SCIP_CALL( SCIPsetIntParam(scip, "presolving/maxrounds", 1) );
900  }
901  else
902  {
903  /* creating the original problem */
904  SCIP_CALL( createOriginalproblem(scip, facilityvars, customervars, capconss, demandconss, &sufficientcap, costs,
905  demands, capacity, fixedcost, ncustomers, nfacilities, nscenarios, quadcosts) );
906  }
907 
908  /* create problem data */
909  SCIP_CALL( probdataCreate(scip, &probdata, subproblems, facilityvars, subfacilityvars, customervars, capconss,
910  demandconss, sufficientcap, costs, demands, capacity, fixedcost, ncustomers, nfacilities, nscenarios,
911  usebenders, quadcosts) );
912 
913  /* set user problem data */
914  SCIP_CALL( SCIPsetProbData(scip, probdata) );
915 
916  /* free local buffer arrays */
917  if( usebenders )
918  {
919  SCIPfreeBufferArray(scip, &subproblems);
920 
921  for( i = nfacilities - 1; i >= 0; i-- )
922  SCIPfreeBufferArray(scip, &subfacilityvars[i]);
923  SCIPfreeBufferArray(scip, &subfacilityvars);
924  }
925 
926  for( i = ncustomers - 1; i >= 0; i-- )
927  {
928  for( j = nfacilities - 1; j >= 0; j-- )
929  SCIPfreeBufferArray(scip, &customervars[i][j]);
930  SCIPfreeBufferArray(scip, &customervars[i]);
931  }
932  SCIPfreeBufferArray(scip, &customervars);
933  SCIPfreeBufferArray(scip, &facilityvars);
934 
935  for( i = nfacilities - 1; i >= 0; i-- )
936  SCIPfreeBufferArray(scip, &capconss[i]);
937  SCIPfreeBufferArray(scip, &capconss);
938 
939  for( i = ncustomers - 1; i >= 0; i-- )
940  SCIPfreeBufferArray(scip, &demandconss[i]);
941  SCIPfreeBufferArray(scip, &demandconss);
942 
943  return SCIP_OKAY;
944 }
945 
946 /** returns the number of facilities */
948  SCIP_PROBDATA* probdata /**< problem data */
949  )
950 {
951  assert(probdata != NULL);
952 
953  return probdata->nfacilities;
954 }
955 
956 /** returns the number of customers */
958  SCIP_PROBDATA* probdata /**< problem data */
959  )
960 {
961  assert(probdata != NULL);
962 
963  return probdata->ncustomers;
964 }
965 
966 /** returns the facility variables */
968  SCIP_PROBDATA* probdata /**< problem data */
969  )
970 {
971  assert(probdata != NULL);
972 
973  return probdata->facilityvars;
974 }
975 
976 /**@} */
#define SCIPfreeBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:110
#define NULL
Definition: def.h:267
#define SCIPallocBlockMemoryArray(scip, ptr, num)
Definition: scip_mem.h:93
SCIP_RETCODE SCIPcreateConsBasicLinear(SCIP *scip, SCIP_CONS **cons, const char *name, int nvars, SCIP_VAR **vars, SCIP_Real *vals, SCIP_Real lhs, SCIP_Real rhs)
#define SCIP_MAXSTRLEN
Definition: def.h:288
#define DEFAULT_SCALINGFACTOR
SCIP_RETCODE SCIPprobdataCreate(SCIP *scip, const char *probname, SCIP_Real **costs, SCIP_Real **demands, SCIP_Real *capacity, SCIP_Real *fixedcost, int ncustomers, int nfacilities, int nscenarios, SCIP_Bool usebenders, SCIP_Bool quadcosts)
SCIP_RETCODE SCIPreleaseVar(SCIP *scip, SCIP_VAR **var)
Definition: scip_var.c:1250
#define FALSE
Definition: def.h:94
SCIP_Real SCIPinfinity(SCIP *scip)
SCIP_RETCODE SCIPcreateBendersDefault(SCIP *scip, SCIP **subproblems, int nsubproblems)
SCIP_VERBLEVEL SCIPgetVerbLevel(SCIP *scip)
Definition: scip_message.c:249
int SCIPsnprintf(char *t, int len, const char *s,...)
Definition: misc.c:10877
#define TRUE
Definition: def.h:93
enum SCIP_Retcode SCIP_RETCODE
Definition: type_retcode.h:63
int SCIPprobdataGetNCustomers(SCIP_PROBDATA *probdata)
SCIP_RETCODE SCIPsetProbData(SCIP *scip, SCIP_PROBDATA *probdata)
Definition: scip_prob.c:1014
static SCIP_DECL_PROBDELORIG(probdelorigScflp)
SCIP_RETCODE SCIPcreateVarBasic(SCIP *scip, SCIP_VAR **var, const char *name, SCIP_Real lb, SCIP_Real ub, SCIP_Real obj, SCIP_VARTYPE vartype)
Definition: scip_var.c:194
#define SCIPfreeBlockMemory(scip, ptr)
Definition: scip_mem.h:108
SCIP_MESSAGEHDLR * SCIPgetMessagehdlr(SCIP *scip)
Definition: scip_message.c:88
#define SCIPfreeBufferArray(scip, ptr)
Definition: scip_mem.h:136
SCIP_RETCODE SCIPcreate(SCIP **scip)
Definition: scip_general.c:307
#define SCIPallocBlockMemory(scip, ptr)
Definition: scip_mem.h:89
#define SCIPdebugMsg
Definition: scip_message.h:78
SCIP_RETCODE SCIPaddCoefLinear(SCIP *scip, SCIP_CONS *cons, SCIP_VAR *var, SCIP_Real val)
void SCIPinfoMessage(SCIP *scip, FILE *file, const char *formatstr,...)
Definition: scip_message.c:208
SCIP_RETCODE SCIPcreateProbBasic(SCIP *scip, const char *name)
Definition: scip_prob.c:180
static SCIP_DECL_PROBTRANS(probtransScflp)
int SCIPprobdataGetNFacilities(SCIP_PROBDATA *probdata)
#define SCIPduplicateBlockMemoryArray(scip, ptr, source, num)
Definition: scip_mem.h:105
SCIP_RETCODE SCIPsetObjsense(SCIP *scip, SCIP_OBJSENSE objsense)
Definition: scip_prob.c:1242
static SCIP_RETCODE createSubproblems(SCIP *scip, SCIP **subproblems, SCIP_VAR **facilityvars, SCIP_VAR ***subfacilityvars, SCIP_VAR ****customervars, SCIP_CONS ***capconss, SCIP_CONS ***demandconss, SCIP_Real **costs, SCIP_Real **demands, SCIP_Real *capacity, SCIP_Real *fixedcost, int ncustomers, int nfacilities, int nscenarios, SCIP_Bool quadcosts)
void SCIPmessagePrintVerbInfo(SCIP_MESSAGEHDLR *messagehdlr, SCIP_VERBLEVEL verblevel, SCIP_VERBLEVEL msgverblevel, const char *formatstr,...)
Definition: message.c:678
SCIP_RETCODE SCIPaddCons(SCIP *scip, SCIP_CONS *cons)
Definition: scip_prob.c:2770
SCIP_RETCODE SCIPsetBoolParam(SCIP *scip, const char *name, SCIP_Bool value)
Definition: scip_param.c:429
SCIP_RETCODE SCIPcreateConsQuadraticNonlinear(SCIP *scip, SCIP_CONS **cons, const char *name, int nlinvars, SCIP_VAR **linvars, SCIP_Real *lincoefs, int nquadterms, SCIP_VAR **quadvars1, SCIP_VAR **quadvars2, SCIP_Real *quadcoefs, SCIP_Real lhs, SCIP_Real rhs, SCIP_Bool initial, SCIP_Bool separate, SCIP_Bool enforce, SCIP_Bool check, SCIP_Bool propagate, SCIP_Bool local, SCIP_Bool modifiable, SCIP_Bool dynamic, SCIP_Bool removable)
#define SCIP_CALL(x)
Definition: def.h:380
Problem data for Stochastic Capacitated Facility Location problem.
static SCIP_RETCODE createOriginalproblem(SCIP *scip, SCIP_VAR **facilityvars, SCIP_VAR ****customervars, SCIP_CONS ***capconss, SCIP_CONS ***demandconss, SCIP_CONS **sufficientcap, SCIP_Real **costs, SCIP_Real **demands, SCIP_Real *capacity, SCIP_Real *fixedcost, int ncustomers, int nfacilities, int nscenarios, SCIP_Bool quadcosts)
#define SCIPallocBufferArray(scip, ptr, num)
Definition: scip_mem.h:124
#define SCIP_Bool
Definition: def.h:91
SCIP_RETCODE SCIPsetProbTrans(SCIP *scip, SCIP_DECL_PROBTRANS((*probtrans)))
Definition: scip_prob.c:221
SCIP_RETCODE SCIPincludeDefaultPlugins(SCIP *scip)
static SCIP_RETCODE probdataFree(SCIP *scip, SCIP_PROBDATA **probdata)
SCIP_RETCODE SCIPsetIntParam(SCIP *scip, const char *name, int value)
Definition: scip_param.c:487
SCIP_VAR ** SCIPprobdataGetFacilityVars(SCIP_PROBDATA *probdata)
static SCIP_DECL_PROBDELTRANS(probdeltransScflp)
struct SCIP_ProbData SCIP_PROBDATA
Definition: type_prob.h:53
SCIP_RETCODE SCIPaddVar(SCIP *scip, SCIP_VAR *var)
Definition: scip_prob.c:1668
SCIP_RETCODE SCIPreleaseCons(SCIP *scip, SCIP_CONS **cons)
Definition: scip_cons.c:1174
static SCIP_RETCODE probdataCreate(SCIP *scip, SCIP_PROBDATA **probdata, SCIP **subproblems, SCIP_VAR **facilityvars, SCIP_VAR ***subfacilityvars, SCIP_VAR ****customervars, SCIP_CONS ***capconss, SCIP_CONS ***demandconss, SCIP_CONS *sufficientcap, SCIP_Real **costs, SCIP_Real **demands, SCIP_Real *capacity, SCIP_Real *fixedcost, int ncustomers, int nfacilities, int nscenarios, SCIP_Bool usebenders, SCIP_Bool quadcosts)
#define SCIP_Real
Definition: def.h:173
static SCIP_RETCODE createMasterproblem(SCIP *scip, SCIP_VAR **facilityvars, SCIP_CONS **sufficientcap, SCIP_Real *capacity, SCIP_Real *fixedcost, SCIP_Real **demands, int ncustomers, int nfacilities, int nscenarios)
SCIP_RETCODE SCIPsetProbDeltrans(SCIP *scip, SCIP_DECL_PROBDELTRANS((*probdeltrans)))
Definition: scip_prob.c:242
SCIP_RETCODE SCIPsetProbDelorig(SCIP *scip, SCIP_DECL_PROBDELORIG((*probdelorig)))
Definition: scip_prob.c:200
default SCIP plugins
SCIP callable library.
SCIP_RETCODE SCIPfree(SCIP **scip)
Definition: scip_general.c:339